人脸生成(Face Generation)

在该项目中,你将使用生成式对抗网络(Generative Adversarial Nets)来生成新的人脸图像。

获取数据

该项目将使用以下数据集:

  • MNIST
  • CelebA

由于 CelebA 数据集比较复杂,而且这是你第一次使用 GANs。我们想让你先在 MNIST 数据集上测试你的 GANs 模型,以让你更快的评估所建立模型的性能。

如果你在使用 FloydHub, 请将 data_dir 设置为 "/input" 并使用 FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".

In [1]:
data_dir = './data'

# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'


"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper

helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Found mnist Data
Found celeba Data

探索数据(Explore the Data)

MNIST

MNIST 是一个手写数字的图像数据集。你可以更改 show_n_images 探索此数据集。

In [2]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot

mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
Out[2]:
<matplotlib.image.AxesImage at 0x7f3b30e06550>

CelebA

CelebFaces Attributes Dataset (CelebA) 是一个包含 20 多万张名人图片及相关图片说明的数据集。你将用此数据集生成人脸,不会用不到相关说明。你可以更改 show_n_images 探索此数据集。

In [3]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Out[3]:
<matplotlib.image.AxesImage at 0x7f3b2dbb5518>

预处理数据(Preprocess the Data)

由于该项目的重点是建立 GANs 模型,我们将为你预处理数据。

经过数据预处理,MNIST 和 CelebA 数据集的值在 28×28 维度图像的 [-0.5, 0.5] 范围内。CelebA 数据集中的图像裁剪了非脸部的图像部分,然后调整到 28x28 维度。

MNIST 数据集中的图像是单通道的黑白图像,CelebA 数据集中的图像是 三通道的 RGB 彩色图像

建立神经网络(Build the Neural Network)

你将通过部署以下函数来建立 GANs 的主要组成部分:

  • model_inputs
  • discriminator
  • generator
  • model_loss
  • model_opt
  • train

检查 TensorFlow 版本并获取 GPU 型号

检查你是否使用正确的 TensorFlow 版本,并获取 GPU 型号

In [4]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf

# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer.  You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))

# Check for a GPU
if not tf.test.gpu_device_name():
    warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
    print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.0.1
/home/fathersucker/.conda/envs/py36/lib/python3.6/site-packages/ipykernel_launcher.py:14: UserWarning: No GPU found. Please use a GPU to train your neural network.
  

输入(Input)

部署 model_inputs 函数以创建用于神经网络的 占位符 (TF Placeholders)。请创建以下占位符:

  • 输入图像占位符: 使用 image_widthimage_heightimage_channels 设置为 rank 4。
  • 输入 Z 占位符: 设置为 rank 2,并命名为 z_dim
  • 学习速率占位符: 设置为 rank 0。

返回占位符元组的形状为 (tensor of real input images, tensor of z data, learning rate)。

In [5]:
import problem_unittests as tests

def model_inputs(image_width, image_height, image_channels, z_dim):
    """
    Create the model inputs
    :param image_width: The input image width
    :param image_height: The input image height
    :param image_channels: The number of image channels
    :param z_dim: The dimension of Z
    :return: Tuple of (tensor of real input images, tensor of z data, learning rate)
    """
    # TODO: Implement Function
    input_images = tf.placeholder(tf.float32,[None,image_width,image_height,image_channels])
    z = tf.placeholder(tf.float32,[None,z_dim])
    learning_rate = tf.placeholder(tf.float32)

    return input_images, z, learning_rate


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Tests Passed

辨别器(Discriminator)

部署 discriminator 函数创建辨别器神经网络以辨别 images。该函数应能够重复使用神经网络中的各种变量。 在 tf.variable_scope 中使用 "discriminator" 的变量空间名来重复使用该函数中的变量。

该函数应返回形如 (tensor output of the discriminator, tensor logits of the discriminator) 的元组。

In [6]:
def discriminator(images, reuse=False):
    """
    Create the discriminator network
    :param image: Tensor of input image(s)
    :param reuse: Boolean if the weights should be reused
    :return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
    """
    # TODO: Implement Function
    with tf.variable_scope('discriminator', reuse=reuse):
        l1 = tf.layers.conv2d(images, 64, 5, strides=2, padding='same',activation=None)
        l1 = tf.nn.relu(l1)
        
        l2 = tf.layers.conv2d(l1, 128, 5, strides=2, padding='same',activation=None)
        l2 = tf.layers.batch_normalization(l2, training=True)
        l2 = tf.nn.relu(l2)
        
        flat = tf.reshape(l2,(-1,7*7*128))
        
        logits = tf.layers.dense(flat, 1)
        out = tf.sigmoid(logits)
        
    return out, logits


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed

生成器(Generator)

部署 generator 函数以使用 z 生成图像。该函数应能够重复使用神经网络中的各种变量。 在 tf.variable_scope 中使用 "generator" 的变量空间名来重复使用该函数中的变量。

该函数应返回所生成的 28 x 28 x out_channel_dim 维度图像。

In [7]:
def generator(z, out_channel_dim, is_train=True):
    """
    Create the generator network
    :param z: Input z
    :param out_channel_dim: The number of channels in the output image
    :param is_train: Boolean if generator is being used for training
    :return: The tensor output of the generator
    """
    # TODO: Implement Function
    with tf.variable_scope('generator',reuse= not is_train):
        x1 = tf.layers.dense(z, (7*7*128))
        
        x1 = tf.reshape(x1, (-1,7,7,128))
        x1 = tf.layers.batch_normalization(x1, training=is_train)
        x1 = tf.nn.relu(x1)
        
        x2 = tf.layers.conv2d_transpose(x1, 64, 5, strides=2, padding='same',activation=None)
        x2 = tf.layers.batch_normalization(x2, training=is_train)
        x2 = tf.nn.relu(x2)
        
        logits = tf.layers.conv2d_transpose(x2, out_channel_dim, 5, strides=2, padding='same')
        
        out = tf.tanh(logits)
    return out


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Tests Passed

损失函数(Loss)

部署 model_loss 函数训练并计算 GANs 的损失。该函数应返回形如 (discriminator loss, generator loss) 的元组。

使用你已实现的函数:

  • discriminator(images, reuse=False)
  • generator(z, out_channel_dim, is_train=True)
In [8]:
def model_loss(input_real, input_z, out_channel_dim):
    """
    Get the loss for the discriminator and generator
    :param input_real: Images from the real dataset
    :param input_z: Z input
    :param out_channel_dim: The number of channels in the output image
    :return: A tuple of (discriminator loss, generator loss)
    """
    # TODO: Implement Function
    g_model = generator(input_z, out_channel_dim)
    d_model_real, d_logits_real = discriminator(input_real)
    d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)

    d_loss_real = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real)))
    d_loss_fake = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
    g_loss = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))

    d_loss = d_loss_real + d_loss_fake
    return d_loss, g_loss


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed

优化(Optimization)

部署 model_opt 函数实现对 GANs 的优化。使用 tf.trainable_variables 获取可训练的所有变量。通过变量空间名 discriminatorgenerator 来过滤变量。该函数应返回形如 (discriminator training operation, generator training operation) 的元组。

In [9]:
def model_opt(d_loss, g_loss, learning_rate, beta1):
    """
    Get optimization operations
    :param d_loss: Discriminator loss Tensor
    :param g_loss: Generator loss Tensor
    :param learning_rate: Learning Rate Placeholder
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :return: A tuple of (discriminator training operation, generator training operation)
    """
    # TODO: Implement Function
    
    t_vars = tf.trainable_variables()
    d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
    g_vars = [var for var in t_vars if var.name.startswith('generator')]

    # Optimize
    with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
        d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
        g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)

    return d_train_opt, g_train_opt


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed

训练神经网络(Neural Network Training)

输出显示

使用该函数可以显示生成器 (Generator) 在训练过程中的当前输出,这会帮你评估 GANs 模型的训练程度。

In [10]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np

def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
    """
    Show example output for the generator
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor
    :param out_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dim = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])

    samples = sess.run(
        generator(input_z, out_channel_dim, False),
        feed_dict={input_z: example_z})

    images_grid = helper.images_square_grid(samples, image_mode)
    pyplot.imshow(images_grid, cmap=cmap)
    pyplot.show()

训练

部署 train 函数以建立并训练 GANs 模型。记得使用以下你已完成的函数:

  • model_inputs(image_width, image_height, image_channels, z_dim)
  • model_loss(input_real, input_z, out_channel_dim)
  • model_opt(d_loss, g_loss, learning_rate, beta1)

使用 show_generator_output 函数显示 generator 在训练过程中的输出。

注意:在每个批次 (batch) 中运行 show_generator_output 函数会显著增加训练时间与该 notebook 的体积。推荐每 100 批次输出一次 generator 的输出。

In [11]:
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode,
          print_every=10, show_every=100):
    """
    Train the GAN
    :param epoch_count: Number of epochs
    :param batch_size: Batch Size
    :param z_dim: Z dimension
    :param learning_rate: Learning Rate
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :param get_batches: Function to get batches
    :param data_shape: Shape of the data
    :param data_image_mode: The image mode to use for images ("RGB" or "L")
    """
    # TODO: Build Model
    input_real, input_z, lr = model_inputs(data_shape[1], data_shape[2], data_shape[3], z_dim)
    d_loss, g_loss = model_loss(input_real, input_z, data_shape[3])
    d_opt, g_opt = model_opt(d_loss, g_loss, learning_rate, beta1)
    
    steps = 0
    
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch_i in range(epoch_count):
            for batch_images in get_batches(batch_size):
                # TODO: Train Model
                steps += 1
                batch_images *= 2.0
                
                batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
                
                _ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z})
                _ = sess.run(g_opt, feed_dict={input_real: batch_images, input_z: batch_z})

                if steps % print_every == 0:
                    train_loss_d = d_loss.eval({input_z: batch_z, input_real: batch_images})
                    train_loss_g = g_loss.eval({input_z: batch_z})

                    print("Epoch {}/{}...".format(epoch_i + 1, epochs),
                          "Discriminator Loss: {:.4f}...".format(train_loss_d),
                          "Generator Loss: {:.4f}".format(train_loss_g))

                if steps % show_every == 0:
                    show_generator_output(sess, 25, input_z, data_shape[3], data_image_mode)

MNIST

在 MNIST 上测试你的 GANs 模型。经过 2 次迭代,GANs 应该能够生成类似手写数字的图像。确保生成器 (generator) 低于辨别器 (discriminator) 的损失,或接近 0。

In [12]:
batch_size = 64
z_dim = 100
learning_rate = 0.0001
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
          mnist_dataset.shape, mnist_dataset.image_mode)
Epoch 1/2... Discriminator Loss: 0.4778... Generator Loss: 1.1916
Epoch 1/2... Discriminator Loss: 0.5480... Generator Loss: 1.1773
Epoch 1/2... Discriminator Loss: 0.5888... Generator Loss: 1.1580
Epoch 1/2... Discriminator Loss: 0.3946... Generator Loss: 1.5073
Epoch 1/2... Discriminator Loss: 0.4791... Generator Loss: 1.4014
Epoch 1/2... Discriminator Loss: 0.4053... Generator Loss: 1.6373
Epoch 1/2... Discriminator Loss: 0.3813... Generator Loss: 1.6793
Epoch 1/2... Discriminator Loss: 0.3726... Generator Loss: 1.7090
Epoch 1/2... Discriminator Loss: 0.2991... Generator Loss: 1.9288
Epoch 1/2... Discriminator Loss: 0.2219... Generator Loss: 2.1729
Epoch 1/2... Discriminator Loss: 0.1799... Generator Loss: 2.4049
Epoch 1/2... Discriminator Loss: 0.2371... Generator Loss: 2.2602
Epoch 1/2... Discriminator Loss: 0.1888... Generator Loss: 2.4098
Epoch 1/2... Discriminator Loss: 0.2503... Generator Loss: 2.1541
Epoch 1/2... Discriminator Loss: 0.2144... Generator Loss: 2.2710
Epoch 1/2... Discriminator Loss: 0.3911... Generator Loss: 1.3805
Epoch 1/2... Discriminator Loss: 0.2729... Generator Loss: 2.1382
Epoch 1/2... Discriminator Loss: 0.3093... Generator Loss: 1.6696
Epoch 1/2... Discriminator Loss: 0.2538... Generator Loss: 2.3615
Epoch 1/2... Discriminator Loss: 0.3486... Generator Loss: 1.8736
Epoch 1/2... Discriminator Loss: 0.5119... Generator Loss: 1.1349
Epoch 1/2... Discriminator Loss: 0.3814... Generator Loss: 2.4089
Epoch 1/2... Discriminator Loss: 0.3917... Generator Loss: 1.7326
Epoch 1/2... Discriminator Loss: 0.3908... Generator Loss: 1.9794
Epoch 1/2... Discriminator Loss: 0.6439... Generator Loss: 0.9421
Epoch 1/2... Discriminator Loss: 0.4641... Generator Loss: 2.6454
Epoch 1/2... Discriminator Loss: 0.4557... Generator Loss: 1.5313
Epoch 1/2... Discriminator Loss: 0.5642... Generator Loss: 2.8049
Epoch 1/2... Discriminator Loss: 0.3637... Generator Loss: 2.0194
Epoch 1/2... Discriminator Loss: 0.5054... Generator Loss: 2.6011
Epoch 1/2... Discriminator Loss: 0.5071... Generator Loss: 1.5168
Epoch 1/2... Discriminator Loss: 0.5156... Generator Loss: 1.3214
Epoch 1/2... Discriminator Loss: 0.4345... Generator Loss: 1.6688
Epoch 1/2... Discriminator Loss: 0.5275... Generator Loss: 1.3794
Epoch 1/2... Discriminator Loss: 0.5123... Generator Loss: 1.6584
Epoch 1/2... Discriminator Loss: 0.5122... Generator Loss: 1.2832
Epoch 1/2... Discriminator Loss: 0.6285... Generator Loss: 1.1257
Epoch 1/2... Discriminator Loss: 0.5892... Generator Loss: 1.9370
Epoch 1/2... Discriminator Loss: 0.5047... Generator Loss: 1.9469
Epoch 1/2... Discriminator Loss: 0.5244... Generator Loss: 1.2226
Epoch 1/2... Discriminator Loss: 0.5000... Generator Loss: 1.7663
Epoch 1/2... Discriminator Loss: 0.5138... Generator Loss: 2.1022
Epoch 1/2... Discriminator Loss: 0.4659... Generator Loss: 1.6894
Epoch 1/2... Discriminator Loss: 0.5157... Generator Loss: 1.6197
Epoch 1/2... Discriminator Loss: 0.5831... Generator Loss: 1.9642
Epoch 1/2... Discriminator Loss: 0.4711... Generator Loss: 1.8212
Epoch 1/2... Discriminator Loss: 0.4862... Generator Loss: 1.4974
Epoch 1/2... Discriminator Loss: 0.5985... Generator Loss: 1.0540
Epoch 1/2... Discriminator Loss: 0.5335... Generator Loss: 1.6596
Epoch 1/2... Discriminator Loss: 0.5469... Generator Loss: 2.3174
Epoch 1/2... Discriminator Loss: 0.5721... Generator Loss: 1.3429
Epoch 1/2... Discriminator Loss: 0.5653... Generator Loss: 1.4922
Epoch 1/2... Discriminator Loss: 0.5216... Generator Loss: 1.5439
Epoch 1/2... Discriminator Loss: 0.4856... Generator Loss: 1.5367
Epoch 1/2... Discriminator Loss: 0.4686... Generator Loss: 1.5876
Epoch 1/2... Discriminator Loss: 0.6336... Generator Loss: 1.0660
Epoch 1/2... Discriminator Loss: 0.6501... Generator Loss: 2.1990
Epoch 1/2... Discriminator Loss: 0.4636... Generator Loss: 1.6885
Epoch 1/2... Discriminator Loss: 0.6133... Generator Loss: 1.1477
Epoch 1/2... Discriminator Loss: 0.5925... Generator Loss: 2.0744
Epoch 1/2... Discriminator Loss: 0.5603... Generator Loss: 1.7738
Epoch 1/2... Discriminator Loss: 0.5028... Generator Loss: 1.6805
Epoch 1/2... Discriminator Loss: 0.5515... Generator Loss: 1.4171
Epoch 1/2... Discriminator Loss: 0.5623... Generator Loss: 2.1914
Epoch 1/2... Discriminator Loss: 0.5017... Generator Loss: 1.6466
Epoch 1/2... Discriminator Loss: 0.5162... Generator Loss: 1.9893
Epoch 1/2... Discriminator Loss: 0.4955... Generator Loss: 1.6433
Epoch 1/2... Discriminator Loss: 0.6376... Generator Loss: 1.0482
Epoch 1/2... Discriminator Loss: 0.4223... Generator Loss: 1.8526
Epoch 1/2... Discriminator Loss: 0.4950... Generator Loss: 1.4660
Epoch 1/2... Discriminator Loss: 0.4720... Generator Loss: 1.4030
Epoch 1/2... Discriminator Loss: 0.5065... Generator Loss: 1.7531
Epoch 1/2... Discriminator Loss: 0.4376... Generator Loss: 1.6950
Epoch 1/2... Discriminator Loss: 0.6066... Generator Loss: 1.1686
Epoch 1/2... Discriminator Loss: 0.4403... Generator Loss: 1.4599
Epoch 1/2... Discriminator Loss: 0.4056... Generator Loss: 1.7417
Epoch 1/2... Discriminator Loss: 0.4509... Generator Loss: 1.7670
Epoch 1/2... Discriminator Loss: 0.4763... Generator Loss: 1.6434
Epoch 1/2... Discriminator Loss: 0.4550... Generator Loss: 1.4863
Epoch 1/2... Discriminator Loss: 0.5327... Generator Loss: 1.3280
Epoch 1/2... Discriminator Loss: 0.5287... Generator Loss: 1.3203
Epoch 1/2... Discriminator Loss: 0.4223... Generator Loss: 1.8771
Epoch 1/2... Discriminator Loss: 0.4745... Generator Loss: 1.6833
Epoch 1/2... Discriminator Loss: 0.4479... Generator Loss: 1.6458
Epoch 1/2... Discriminator Loss: 0.4044... Generator Loss: 1.5945
Epoch 1/2... Discriminator Loss: 0.3917... Generator Loss: 1.9808
Epoch 1/2... Discriminator Loss: 0.4171... Generator Loss: 2.3469
Epoch 1/2... Discriminator Loss: 0.4601... Generator Loss: 1.6320
Epoch 1/2... Discriminator Loss: 0.4528... Generator Loss: 1.7788
Epoch 1/2... Discriminator Loss: 0.3743... Generator Loss: 1.8756
Epoch 1/2... Discriminator Loss: 0.4750... Generator Loss: 1.5708
Epoch 1/2... Discriminator Loss: 0.4424... Generator Loss: 1.7598
Epoch 1/2... Discriminator Loss: 0.4816... Generator Loss: 1.5083
Epoch 2/2... Discriminator Loss: 0.4503... Generator Loss: 1.7561
Epoch 2/2... Discriminator Loss: 0.4876... Generator Loss: 1.4442
Epoch 2/2... Discriminator Loss: 0.4809... Generator Loss: 1.6904
Epoch 2/2... Discriminator Loss: 0.5164... Generator Loss: 1.9909
Epoch 2/2... Discriminator Loss: 0.6446... Generator Loss: 1.0688
Epoch 2/2... Discriminator Loss: 0.3791... Generator Loss: 2.0790
Epoch 2/2... Discriminator Loss: 0.4939... Generator Loss: 2.2316
Epoch 2/2... Discriminator Loss: 0.5230... Generator Loss: 1.6094
Epoch 2/2... Discriminator Loss: 0.4966... Generator Loss: 1.5252
Epoch 2/2... Discriminator Loss: 0.4048... Generator Loss: 1.9428
Epoch 2/2... Discriminator Loss: 0.4597... Generator Loss: 1.9608
Epoch 2/2... Discriminator Loss: 0.4673... Generator Loss: 1.5864
Epoch 2/2... Discriminator Loss: 0.4486... Generator Loss: 1.7868
Epoch 2/2... Discriminator Loss: 0.5326... Generator Loss: 1.3408
Epoch 2/2... Discriminator Loss: 0.5185... Generator Loss: 1.3335
Epoch 2/2... Discriminator Loss: 0.4619... Generator Loss: 1.6757
Epoch 2/2... Discriminator Loss: 0.4288... Generator Loss: 1.7050
Epoch 2/2... Discriminator Loss: 0.4777... Generator Loss: 1.6729
Epoch 2/2... Discriminator Loss: 0.5355... Generator Loss: 1.5216
Epoch 2/2... Discriminator Loss: 0.5949... Generator Loss: 1.8531
Epoch 2/2... Discriminator Loss: 0.5440... Generator Loss: 2.3863
Epoch 2/2... Discriminator Loss: 0.4669... Generator Loss: 2.1425
Epoch 2/2... Discriminator Loss: 0.6361... Generator Loss: 1.0535
Epoch 2/2... Discriminator Loss: 0.4870... Generator Loss: 1.4178
Epoch 2/2... Discriminator Loss: 0.5067... Generator Loss: 1.3809
Epoch 2/2... Discriminator Loss: 0.4970... Generator Loss: 1.8671
Epoch 2/2... Discriminator Loss: 0.5841... Generator Loss: 1.8253
Epoch 2/2... Discriminator Loss: 0.5910... Generator Loss: 1.1484
Epoch 2/2... Discriminator Loss: 0.5365... Generator Loss: 1.8585
Epoch 2/2... Discriminator Loss: 0.4352... Generator Loss: 2.0967
Epoch 2/2... Discriminator Loss: 0.4208... Generator Loss: 1.7419
Epoch 2/2... Discriminator Loss: 0.5468... Generator Loss: 1.1856
Epoch 2/2... Discriminator Loss: 0.5264... Generator Loss: 1.7437
Epoch 2/2... Discriminator Loss: 0.6794... Generator Loss: 0.9680
Epoch 2/2... Discriminator Loss: 0.6077... Generator Loss: 1.2515
Epoch 2/2... Discriminator Loss: 0.5483... Generator Loss: 2.0486
Epoch 2/2... Discriminator Loss: 0.5240... Generator Loss: 1.7192
Epoch 2/2... Discriminator Loss: 0.4896... Generator Loss: 1.9042
Epoch 2/2... Discriminator Loss: 0.5788... Generator Loss: 1.2484
Epoch 2/2... Discriminator Loss: 0.4709... Generator Loss: 1.5571
Epoch 2/2... Discriminator Loss: 0.5469... Generator Loss: 1.3265
Epoch 2/2... Discriminator Loss: 0.6803... Generator Loss: 1.1381
Epoch 2/2... Discriminator Loss: 0.4216... Generator Loss: 1.8321
Epoch 2/2... Discriminator Loss: 0.6630... Generator Loss: 2.3556
Epoch 2/2... Discriminator Loss: 0.6262... Generator Loss: 2.3629
Epoch 2/2... Discriminator Loss: 0.6095... Generator Loss: 1.4953
Epoch 2/2... Discriminator Loss: 0.4958... Generator Loss: 1.9588
Epoch 2/2... Discriminator Loss: 0.6098... Generator Loss: 1.2148
Epoch 2/2... Discriminator Loss: 0.5903... Generator Loss: 1.1982
Epoch 2/2... Discriminator Loss: 0.5563... Generator Loss: 2.0028
Epoch 2/2... Discriminator Loss: 0.6779... Generator Loss: 1.8720
Epoch 2/2... Discriminator Loss: 0.4805... Generator Loss: 1.7773
Epoch 2/2... Discriminator Loss: 0.5431... Generator Loss: 1.7697
Epoch 2/2... Discriminator Loss: 0.6439... Generator Loss: 1.1841
Epoch 2/2... Discriminator Loss: 0.5469... Generator Loss: 1.8939
Epoch 2/2... Discriminator Loss: 0.5717... Generator Loss: 1.3974
Epoch 2/2... Discriminator Loss: 0.7324... Generator Loss: 1.0300
Epoch 2/2... Discriminator Loss: 0.5812... Generator Loss: 1.3614
Epoch 2/2... Discriminator Loss: 0.7428... Generator Loss: 0.9360
Epoch 2/2... Discriminator Loss: 0.5411... Generator Loss: 1.6979
Epoch 2/2... Discriminator Loss: 0.5215... Generator Loss: 2.0986
Epoch 2/2... Discriminator Loss: 0.5777... Generator Loss: 1.8630
Epoch 2/2... Discriminator Loss: 0.6298... Generator Loss: 1.1208
Epoch 2/2... Discriminator Loss: 0.5076... Generator Loss: 1.7220
Epoch 2/2... Discriminator Loss: 0.6129... Generator Loss: 1.7321
Epoch 2/2... Discriminator Loss: 0.5518... Generator Loss: 1.5768
Epoch 2/2... Discriminator Loss: 0.5727... Generator Loss: 2.1012
Epoch 2/2... Discriminator Loss: 0.7132... Generator Loss: 1.0155
Epoch 2/2... Discriminator Loss: 0.6113... Generator Loss: 1.6653
Epoch 2/2... Discriminator Loss: 0.6185... Generator Loss: 1.1246
Epoch 2/2... Discriminator Loss: 0.5044... Generator Loss: 1.6593
Epoch 2/2... Discriminator Loss: 0.6914... Generator Loss: 1.8991
Epoch 2/2... Discriminator Loss: 0.6666... Generator Loss: 1.0555
Epoch 2/2... Discriminator Loss: 0.7003... Generator Loss: 0.9775
Epoch 2/2... Discriminator Loss: 0.6166... Generator Loss: 1.6577
Epoch 2/2... Discriminator Loss: 0.4987... Generator Loss: 1.7149
Epoch 2/2... Discriminator Loss: 0.6414... Generator Loss: 1.1868
Epoch 2/2... Discriminator Loss: 0.6321... Generator Loss: 1.1371
Epoch 2/2... Discriminator Loss: 0.5605... Generator Loss: 1.5602
Epoch 2/2... Discriminator Loss: 0.6135... Generator Loss: 1.1435
Epoch 2/2... Discriminator Loss: 0.5309... Generator Loss: 1.4601
Epoch 2/2... Discriminator Loss: 0.5720... Generator Loss: 1.9932
Epoch 2/2... Discriminator Loss: 0.6340... Generator Loss: 1.6898
Epoch 2/2... Discriminator Loss: 0.6327... Generator Loss: 1.3364
Epoch 2/2... Discriminator Loss: 0.6593... Generator Loss: 1.3690
Epoch 2/2... Discriminator Loss: 0.5272... Generator Loss: 1.7409
Epoch 2/2... Discriminator Loss: 0.6419... Generator Loss: 1.6086
Epoch 2/2... Discriminator Loss: 0.5713... Generator Loss: 1.4888
Epoch 2/2... Discriminator Loss: 0.5712... Generator Loss: 1.4266
Epoch 2/2... Discriminator Loss: 0.5009... Generator Loss: 1.8928
Epoch 2/2... Discriminator Loss: 0.4526... Generator Loss: 1.7855
Epoch 2/2... Discriminator Loss: 0.5960... Generator Loss: 1.2844
Epoch 2/2... Discriminator Loss: 0.6588... Generator Loss: 1.5591
Epoch 2/2... Discriminator Loss: 0.6014... Generator Loss: 1.4035

CelebA

在 CelebA 上运行你的 GANs 模型。在一般的GPU上运行每次迭代大约需要 20 分钟。你可以运行整个迭代,或者当 GANs 开始产生真实人脸图像时停止它。

In [13]:
batch_size = 32
z_dim = 100
learning_rate = 0.0002
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1

celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
          celeba_dataset.shape, celeba_dataset.image_mode)
Epoch 1/1... Discriminator Loss: 0.8929... Generator Loss: 0.7770
Epoch 1/1... Discriminator Loss: 0.4669... Generator Loss: 1.3237
Epoch 1/1... Discriminator Loss: 0.3794... Generator Loss: 1.5612
Epoch 1/1... Discriminator Loss: 0.3068... Generator Loss: 1.7031
Epoch 1/1... Discriminator Loss: 0.2969... Generator Loss: 1.6860
Epoch 1/1... Discriminator Loss: 0.1949... Generator Loss: 2.4197
Epoch 1/1... Discriminator Loss: 0.1999... Generator Loss: 2.0789
Epoch 1/1... Discriminator Loss: 0.1625... Generator Loss: 2.3025
Epoch 1/1... Discriminator Loss: 0.1050... Generator Loss: 2.6635
Epoch 1/1... Discriminator Loss: 0.5762... Generator Loss: 0.9581
Epoch 1/1... Discriminator Loss: 0.3270... Generator Loss: 1.7290
Epoch 1/1... Discriminator Loss: 0.3461... Generator Loss: 2.4732
Epoch 1/1... Discriminator Loss: 0.3939... Generator Loss: 2.0279
Epoch 1/1... Discriminator Loss: 0.3701... Generator Loss: 2.2255
Epoch 1/1... Discriminator Loss: 0.4203... Generator Loss: 1.6282
Epoch 1/1... Discriminator Loss: 0.4017... Generator Loss: 1.8714
Epoch 1/1... Discriminator Loss: 0.3006... Generator Loss: 2.6669
Epoch 1/1... Discriminator Loss: 0.5698... Generator Loss: 2.5010
Epoch 1/1... Discriminator Loss: 0.3009... Generator Loss: 2.5008
Epoch 1/1... Discriminator Loss: 0.4545... Generator Loss: 1.6723
Epoch 1/1... Discriminator Loss: 0.5531... Generator Loss: 3.4035
Epoch 1/1... Discriminator Loss: 0.4739... Generator Loss: 1.8494
Epoch 1/1... Discriminator Loss: 0.2786... Generator Loss: 2.2639
Epoch 1/1... Discriminator Loss: 0.4607... Generator Loss: 1.7805
Epoch 1/1... Discriminator Loss: 0.4723... Generator Loss: 1.7547
Epoch 1/1... Discriminator Loss: 0.5118... Generator Loss: 1.9175
Epoch 1/1... Discriminator Loss: 0.3925... Generator Loss: 1.8511
Epoch 1/1... Discriminator Loss: 0.5346... Generator Loss: 1.3347
Epoch 1/1... Discriminator Loss: 0.4683... Generator Loss: 2.6058
Epoch 1/1... Discriminator Loss: 0.6398... Generator Loss: 1.1428
Epoch 1/1... Discriminator Loss: 0.5244... Generator Loss: 1.6496
Epoch 1/1... Discriminator Loss: 1.6331... Generator Loss: 3.4740
Epoch 1/1... Discriminator Loss: 0.5730... Generator Loss: 1.4151
Epoch 1/1... Discriminator Loss: 0.5475... Generator Loss: 1.3580
Epoch 1/1... Discriminator Loss: 1.0324... Generator Loss: 0.6576
Epoch 1/1... Discriminator Loss: 0.6066... Generator Loss: 1.1178
Epoch 1/1... Discriminator Loss: 0.5198... Generator Loss: 1.4686
Epoch 1/1... Discriminator Loss: 0.6411... Generator Loss: 1.1169
Epoch 1/1... Discriminator Loss: 0.5858... Generator Loss: 1.6580
Epoch 1/1... Discriminator Loss: 0.5153... Generator Loss: 1.8344
Epoch 1/1... Discriminator Loss: 0.8495... Generator Loss: 0.6995
Epoch 1/1... Discriminator Loss: 0.6458... Generator Loss: 1.2114
Epoch 1/1... Discriminator Loss: 0.7318... Generator Loss: 0.9111
Epoch 1/1... Discriminator Loss: 0.5454... Generator Loss: 1.6748
Epoch 1/1... Discriminator Loss: 0.7312... Generator Loss: 1.5257
Epoch 1/1... Discriminator Loss: 0.5910... Generator Loss: 1.3999
Epoch 1/1... Discriminator Loss: 0.6422... Generator Loss: 1.4072
Epoch 1/1... Discriminator Loss: 0.5901... Generator Loss: 1.2952
Epoch 1/1... Discriminator Loss: 0.5856... Generator Loss: 1.3113
Epoch 1/1... Discriminator Loss: 0.6519... Generator Loss: 1.0779
Epoch 1/1... Discriminator Loss: 0.6351... Generator Loss: 1.4016
Epoch 1/1... Discriminator Loss: 0.6050... Generator Loss: 1.5848
Epoch 1/1... Discriminator Loss: 0.6036... Generator Loss: 1.3848
Epoch 1/1... Discriminator Loss: 0.4006... Generator Loss: 1.6707
Epoch 1/1... Discriminator Loss: 0.6996... Generator Loss: 1.2821
Epoch 1/1... Discriminator Loss: 0.5487... Generator Loss: 1.4331
Epoch 1/1... Discriminator Loss: 0.8861... Generator Loss: 0.8766
Epoch 1/1... Discriminator Loss: 0.6636... Generator Loss: 1.7983
Epoch 1/1... Discriminator Loss: 0.5265... Generator Loss: 1.3862
Epoch 1/1... Discriminator Loss: 0.9548... Generator Loss: 0.6523
Epoch 1/1... Discriminator Loss: 0.6009... Generator Loss: 1.2226
Epoch 1/1... Discriminator Loss: 1.2236... Generator Loss: 0.4501
Epoch 1/1... Discriminator Loss: 0.5669... Generator Loss: 1.2788
Epoch 1/1... Discriminator Loss: 0.7318... Generator Loss: 0.9366
Epoch 1/1... Discriminator Loss: 0.7082... Generator Loss: 1.1676
Epoch 1/1... Discriminator Loss: 0.5621... Generator Loss: 1.6431
Epoch 1/1... Discriminator Loss: 0.8765... Generator Loss: 0.7806
Epoch 1/1... Discriminator Loss: 0.7401... Generator Loss: 1.4296
Epoch 1/1... Discriminator Loss: 0.6651... Generator Loss: 1.4228
Epoch 1/1... Discriminator Loss: 1.0840... Generator Loss: 0.5434
Epoch 1/1... Discriminator Loss: 0.6960... Generator Loss: 1.0724
Epoch 1/1... Discriminator Loss: 0.7352... Generator Loss: 1.3542
Epoch 1/1... Discriminator Loss: 0.7949... Generator Loss: 1.0261
Epoch 1/1... Discriminator Loss: 0.6984... Generator Loss: 1.1259
Epoch 1/1... Discriminator Loss: 1.0556... Generator Loss: 0.6853
Epoch 1/1... Discriminator Loss: 0.7232... Generator Loss: 1.5645
Epoch 1/1... Discriminator Loss: 0.7551... Generator Loss: 1.1243
Epoch 1/1... Discriminator Loss: 0.9449... Generator Loss: 1.1576
Epoch 1/1... Discriminator Loss: 0.6922... Generator Loss: 1.5446
Epoch 1/1... Discriminator Loss: 0.8314... Generator Loss: 0.8954
Epoch 1/1... Discriminator Loss: 0.9408... Generator Loss: 0.8800
Epoch 1/1... Discriminator Loss: 0.8017... Generator Loss: 1.0353
Epoch 1/1... Discriminator Loss: 0.9803... Generator Loss: 0.6486
Epoch 1/1... Discriminator Loss: 0.7323... Generator Loss: 1.1695
Epoch 1/1... Discriminator Loss: 0.7839... Generator Loss: 1.9052
Epoch 1/1... Discriminator Loss: 0.9681... Generator Loss: 0.8208
Epoch 1/1... Discriminator Loss: 0.8334... Generator Loss: 0.9494
Epoch 1/1... Discriminator Loss: 0.7791... Generator Loss: 1.1111
Epoch 1/1... Discriminator Loss: 0.8149... Generator Loss: 1.0720
Epoch 1/1... Discriminator Loss: 0.7172... Generator Loss: 1.0873
Epoch 1/1... Discriminator Loss: 0.7726... Generator Loss: 1.6664
Epoch 1/1... Discriminator Loss: 0.9294... Generator Loss: 1.3110
Epoch 1/1... Discriminator Loss: 1.0274... Generator Loss: 0.6888
Epoch 1/1... Discriminator Loss: 0.9117... Generator Loss: 0.7753
Epoch 1/1... Discriminator Loss: 0.8680... Generator Loss: 1.0371
Epoch 1/1... Discriminator Loss: 0.8701... Generator Loss: 1.4633
Epoch 1/1... Discriminator Loss: 0.9584... Generator Loss: 0.7998
Epoch 1/1... Discriminator Loss: 0.9357... Generator Loss: 1.2062
Epoch 1/1... Discriminator Loss: 0.8686... Generator Loss: 1.1202
Epoch 1/1... Discriminator Loss: 1.3333... Generator Loss: 0.3856
Epoch 1/1... Discriminator Loss: 1.0784... Generator Loss: 0.6778
Epoch 1/1... Discriminator Loss: 0.7552... Generator Loss: 1.1430
Epoch 1/1... Discriminator Loss: 0.8050... Generator Loss: 1.0589
Epoch 1/1... Discriminator Loss: 0.7164... Generator Loss: 1.3789
Epoch 1/1... Discriminator Loss: 0.8896... Generator Loss: 1.1163
Epoch 1/1... Discriminator Loss: 1.0977... Generator Loss: 0.7434
Epoch 1/1... Discriminator Loss: 0.9858... Generator Loss: 0.9329
Epoch 1/1... Discriminator Loss: 0.8262... Generator Loss: 1.1698
Epoch 1/1... Discriminator Loss: 0.8887... Generator Loss: 0.7746
Epoch 1/1... Discriminator Loss: 0.7541... Generator Loss: 1.1540
Epoch 1/1... Discriminator Loss: 0.6959... Generator Loss: 1.0860
Epoch 1/1... Discriminator Loss: 0.7687... Generator Loss: 1.5847
Epoch 1/1... Discriminator Loss: 1.0381... Generator Loss: 0.8305
Epoch 1/1... Discriminator Loss: 0.8914... Generator Loss: 0.8534
Epoch 1/1... Discriminator Loss: 1.0029... Generator Loss: 0.6821
Epoch 1/1... Discriminator Loss: 0.8068... Generator Loss: 1.8453
Epoch 1/1... Discriminator Loss: 0.8752... Generator Loss: 0.9449
Epoch 1/1... Discriminator Loss: 0.8964... Generator Loss: 1.0826
Epoch 1/1... Discriminator Loss: 0.7713... Generator Loss: 1.2169
Epoch 1/1... Discriminator Loss: 1.0099... Generator Loss: 0.8759
Epoch 1/1... Discriminator Loss: 0.9931... Generator Loss: 0.6344
Epoch 1/1... Discriminator Loss: 1.0528... Generator Loss: 0.7054
Epoch 1/1... Discriminator Loss: 0.8992... Generator Loss: 0.9866
Epoch 1/1... Discriminator Loss: 0.8356... Generator Loss: 1.0581
Epoch 1/1... Discriminator Loss: 1.0539... Generator Loss: 0.7003
Epoch 1/1... Discriminator Loss: 0.8024... Generator Loss: 1.2702
Epoch 1/1... Discriminator Loss: 0.9252... Generator Loss: 1.3711
Epoch 1/1... Discriminator Loss: 1.1970... Generator Loss: 0.5885
Epoch 1/1... Discriminator Loss: 1.0500... Generator Loss: 1.2239
Epoch 1/1... Discriminator Loss: 0.7999... Generator Loss: 1.2897
Epoch 1/1... Discriminator Loss: 0.6433... Generator Loss: 1.8292
Epoch 1/1... Discriminator Loss: 1.0557... Generator Loss: 0.9551
Epoch 1/1... Discriminator Loss: 0.8003... Generator Loss: 1.3051
Epoch 1/1... Discriminator Loss: 0.9143... Generator Loss: 0.8210
Epoch 1/1... Discriminator Loss: 0.6552... Generator Loss: 1.4771
Epoch 1/1... Discriminator Loss: 0.7616... Generator Loss: 1.0221
Epoch 1/1... Discriminator Loss: 0.8812... Generator Loss: 1.5021
Epoch 1/1... Discriminator Loss: 0.6123... Generator Loss: 2.4888
Epoch 1/1... Discriminator Loss: 1.1669... Generator Loss: 0.5524
Epoch 1/1... Discriminator Loss: 0.8366... Generator Loss: 1.5843
Epoch 1/1... Discriminator Loss: 0.9968... Generator Loss: 0.7967
Epoch 1/1... Discriminator Loss: 0.8494... Generator Loss: 1.7306
Epoch 1/1... Discriminator Loss: 0.9817... Generator Loss: 0.7410
Epoch 1/1... Discriminator Loss: 1.1189... Generator Loss: 0.6092
Epoch 1/1... Discriminator Loss: 0.8532... Generator Loss: 1.2113
Epoch 1/1... Discriminator Loss: 0.9256... Generator Loss: 0.8211
Epoch 1/1... Discriminator Loss: 0.7877... Generator Loss: 1.3762
Epoch 1/1... Discriminator Loss: 0.9942... Generator Loss: 1.2056
Epoch 1/1... Discriminator Loss: 0.6524... Generator Loss: 1.3692
Epoch 1/1... Discriminator Loss: 0.8354... Generator Loss: 1.0190
Epoch 1/1... Discriminator Loss: 1.0127... Generator Loss: 1.1416
Epoch 1/1... Discriminator Loss: 1.0062... Generator Loss: 0.9157
Epoch 1/1... Discriminator Loss: 0.9610... Generator Loss: 0.8893
Epoch 1/1... Discriminator Loss: 0.9318... Generator Loss: 0.9070
Epoch 1/1... Discriminator Loss: 0.6883... Generator Loss: 1.2226
Epoch 1/1... Discriminator Loss: 0.8009... Generator Loss: 1.5062
Epoch 1/1... Discriminator Loss: 0.6777... Generator Loss: 1.4798
Epoch 1/1... Discriminator Loss: 0.5476... Generator Loss: 1.5313
Epoch 1/1... Discriminator Loss: 0.9227... Generator Loss: 0.7539
Epoch 1/1... Discriminator Loss: 0.8225... Generator Loss: 0.9539
Epoch 1/1... Discriminator Loss: 0.8735... Generator Loss: 1.2031
Epoch 1/1... Discriminator Loss: 0.9928... Generator Loss: 1.1000
Epoch 1/1... Discriminator Loss: 0.9317... Generator Loss: 1.0118
Epoch 1/1... Discriminator Loss: 0.8537... Generator Loss: 0.9534
Epoch 1/1... Discriminator Loss: 0.9587... Generator Loss: 1.1805
Epoch 1/1... Discriminator Loss: 0.7325... Generator Loss: 1.2080
Epoch 1/1... Discriminator Loss: 0.6931... Generator Loss: 1.3197
Epoch 1/1... Discriminator Loss: 0.9848... Generator Loss: 0.8023
Epoch 1/1... Discriminator Loss: 0.7126... Generator Loss: 2.1504
Epoch 1/1... Discriminator Loss: 0.8808... Generator Loss: 1.8875
Epoch 1/1... Discriminator Loss: 0.8972... Generator Loss: 0.8728
Epoch 1/1... Discriminator Loss: 0.8564... Generator Loss: 0.7889
Epoch 1/1... Discriminator Loss: 0.7419... Generator Loss: 1.1586
Epoch 1/1... Discriminator Loss: 1.0236... Generator Loss: 1.2103
Epoch 1/1... Discriminator Loss: 1.0051... Generator Loss: 1.3485
Epoch 1/1... Discriminator Loss: 0.7374... Generator Loss: 1.7976
Epoch 1/1... Discriminator Loss: 0.9785... Generator Loss: 1.0750
Epoch 1/1... Discriminator Loss: 1.1944... Generator Loss: 0.6090
Epoch 1/1... Discriminator Loss: 0.8632... Generator Loss: 0.8761
Epoch 1/1... Discriminator Loss: 1.0651... Generator Loss: 0.7323
Epoch 1/1... Discriminator Loss: 1.0950... Generator Loss: 0.6767
Epoch 1/1... Discriminator Loss: 0.9711... Generator Loss: 0.9193
Epoch 1/1... Discriminator Loss: 0.7844... Generator Loss: 1.3294
Epoch 1/1... Discriminator Loss: 0.9090... Generator Loss: 0.9576
Epoch 1/1... Discriminator Loss: 0.9145... Generator Loss: 0.9680
Epoch 1/1... Discriminator Loss: 1.1715... Generator Loss: 0.6001
Epoch 1/1... Discriminator Loss: 0.8566... Generator Loss: 1.3343
Epoch 1/1... Discriminator Loss: 0.9855... Generator Loss: 0.8504
Epoch 1/1... Discriminator Loss: 0.5808... Generator Loss: 1.5518
Epoch 1/1... Discriminator Loss: 0.7893... Generator Loss: 1.4581
Epoch 1/1... Discriminator Loss: 0.9971... Generator Loss: 0.8413
Epoch 1/1... Discriminator Loss: 0.6973... Generator Loss: 1.2107
Epoch 1/1... Discriminator Loss: 0.9831... Generator Loss: 1.2597
Epoch 1/1... Discriminator Loss: 1.0682... Generator Loss: 0.6129
Epoch 1/1... Discriminator Loss: 1.1646... Generator Loss: 0.7978
Epoch 1/1... Discriminator Loss: 0.8542... Generator Loss: 1.0800
Epoch 1/1... Discriminator Loss: 1.0905... Generator Loss: 0.6315
Epoch 1/1... Discriminator Loss: 1.0075... Generator Loss: 1.3246
Epoch 1/1... Discriminator Loss: 1.3623... Generator Loss: 0.4395
Epoch 1/1... Discriminator Loss: 0.6926... Generator Loss: 1.2589
Epoch 1/1... Discriminator Loss: 0.6576... Generator Loss: 1.2991
Epoch 1/1... Discriminator Loss: 1.1429... Generator Loss: 0.5235
Epoch 1/1... Discriminator Loss: 0.6234... Generator Loss: 1.2331
Epoch 1/1... Discriminator Loss: 0.9002... Generator Loss: 1.4528
Epoch 1/1... Discriminator Loss: 0.8360... Generator Loss: 0.9598
Epoch 1/1... Discriminator Loss: 1.1238... Generator Loss: 0.7627
Epoch 1/1... Discriminator Loss: 0.3990... Generator Loss: 1.9146
Epoch 1/1... Discriminator Loss: 0.7204... Generator Loss: 1.3767
Epoch 1/1... Discriminator Loss: 0.8330... Generator Loss: 1.4445
Epoch 1/1... Discriminator Loss: 1.0544... Generator Loss: 0.6695
Epoch 1/1... Discriminator Loss: 0.7493... Generator Loss: 1.2023
Epoch 1/1... Discriminator Loss: 0.8772... Generator Loss: 1.5969
Epoch 1/1... Discriminator Loss: 0.7753... Generator Loss: 1.2304
Epoch 1/1... Discriminator Loss: 0.9955... Generator Loss: 0.7361
Epoch 1/1... Discriminator Loss: 1.3688... Generator Loss: 0.4450
Epoch 1/1... Discriminator Loss: 1.0324... Generator Loss: 0.7208
Epoch 1/1... Discriminator Loss: 0.7839... Generator Loss: 1.0376
Epoch 1/1... Discriminator Loss: 0.9249... Generator Loss: 0.9056
Epoch 1/1... Discriminator Loss: 0.6038... Generator Loss: 1.2104
Epoch 1/1... Discriminator Loss: 0.8059... Generator Loss: 1.2111
Epoch 1/1... Discriminator Loss: 0.8967... Generator Loss: 0.9605
Epoch 1/1... Discriminator Loss: 0.9063... Generator Loss: 0.8100
Epoch 1/1... Discriminator Loss: 1.1777... Generator Loss: 0.5237
Epoch 1/1... Discriminator Loss: 0.7324... Generator Loss: 1.5929
Epoch 1/1... Discriminator Loss: 0.7972... Generator Loss: 0.9432
Epoch 1/1... Discriminator Loss: 0.7934... Generator Loss: 1.3423
Epoch 1/1... Discriminator Loss: 0.6802... Generator Loss: 1.1818
Epoch 1/1... Discriminator Loss: 0.8176... Generator Loss: 2.0243
Epoch 1/1... Discriminator Loss: 0.5207... Generator Loss: 1.7600
Epoch 1/1... Discriminator Loss: 0.8717... Generator Loss: 1.0017
Epoch 1/1... Discriminator Loss: 1.0561... Generator Loss: 1.1517
Epoch 1/1... Discriminator Loss: 0.7885... Generator Loss: 1.0762
Epoch 1/1... Discriminator Loss: 1.4298... Generator Loss: 0.4418
Epoch 1/1... Discriminator Loss: 0.9834... Generator Loss: 0.7699
Epoch 1/1... Discriminator Loss: 1.0882... Generator Loss: 0.6259
Epoch 1/1... Discriminator Loss: 1.0242... Generator Loss: 0.9453
Epoch 1/1... Discriminator Loss: 0.9903... Generator Loss: 1.2256
Epoch 1/1... Discriminator Loss: 1.0511... Generator Loss: 1.0546
Epoch 1/1... Discriminator Loss: 1.0459... Generator Loss: 0.6384
Epoch 1/1... Discriminator Loss: 1.0679... Generator Loss: 0.7908
Epoch 1/1... Discriminator Loss: 0.9289... Generator Loss: 0.8334
Epoch 1/1... Discriminator Loss: 0.8661... Generator Loss: 1.5793
Epoch 1/1... Discriminator Loss: 0.5740... Generator Loss: 1.3612
Epoch 1/1... Discriminator Loss: 0.7671... Generator Loss: 1.2112
Epoch 1/1... Discriminator Loss: 1.0136... Generator Loss: 0.9667
Epoch 1/1... Discriminator Loss: 1.6049... Generator Loss: 0.3467
Epoch 1/1... Discriminator Loss: 0.7782... Generator Loss: 1.1161
Epoch 1/1... Discriminator Loss: 0.8359... Generator Loss: 1.2246
Epoch 1/1... Discriminator Loss: 0.8498... Generator Loss: 1.0649
Epoch 1/1... Discriminator Loss: 0.9006... Generator Loss: 0.8934
Epoch 1/1... Discriminator Loss: 0.6937... Generator Loss: 1.1086
Epoch 1/1... Discriminator Loss: 0.8486... Generator Loss: 0.9145
Epoch 1/1... Discriminator Loss: 1.0855... Generator Loss: 0.7678
Epoch 1/1... Discriminator Loss: 1.1187... Generator Loss: 0.9654
Epoch 1/1... Discriminator Loss: 1.1330... Generator Loss: 0.5849
Epoch 1/1... Discriminator Loss: 1.1695... Generator Loss: 0.6078
Epoch 1/1... Discriminator Loss: 0.6915... Generator Loss: 1.0545
Epoch 1/1... Discriminator Loss: 1.1535... Generator Loss: 0.6918
Epoch 1/1... Discriminator Loss: 0.9926... Generator Loss: 0.8247
Epoch 1/1... Discriminator Loss: 0.8566... Generator Loss: 1.2724
Epoch 1/1... Discriminator Loss: 0.9049... Generator Loss: 0.9956
Epoch 1/1... Discriminator Loss: 0.5051... Generator Loss: 1.5672
Epoch 1/1... Discriminator Loss: 1.1699... Generator Loss: 0.6173
Epoch 1/1... Discriminator Loss: 0.8842... Generator Loss: 1.8881
Epoch 1/1... Discriminator Loss: 0.8086... Generator Loss: 0.8841
Epoch 1/1... Discriminator Loss: 0.7933... Generator Loss: 1.3217
Epoch 1/1... Discriminator Loss: 1.0916... Generator Loss: 0.8108
Epoch 1/1... Discriminator Loss: 0.8205... Generator Loss: 0.8925
Epoch 1/1... Discriminator Loss: 0.7503... Generator Loss: 1.0451
Epoch 1/1... Discriminator Loss: 1.0876... Generator Loss: 0.5947
Epoch 1/1... Discriminator Loss: 0.6986... Generator Loss: 1.5804
Epoch 1/1... Discriminator Loss: 1.0251... Generator Loss: 0.8749
Epoch 1/1... Discriminator Loss: 0.9744... Generator Loss: 0.6593
Epoch 1/1... Discriminator Loss: 1.1720... Generator Loss: 0.5770
Epoch 1/1... Discriminator Loss: 0.8205... Generator Loss: 1.2333
Epoch 1/1... Discriminator Loss: 0.8071... Generator Loss: 1.1601
Epoch 1/1... Discriminator Loss: 1.1625... Generator Loss: 0.5578
Epoch 1/1... Discriminator Loss: 0.9121... Generator Loss: 0.8163
Epoch 1/1... Discriminator Loss: 0.8635... Generator Loss: 1.1131
Epoch 1/1... Discriminator Loss: 0.9648... Generator Loss: 0.7045
Epoch 1/1... Discriminator Loss: 1.2997... Generator Loss: 0.5126
Epoch 1/1... Discriminator Loss: 0.9550... Generator Loss: 0.8319
Epoch 1/1... Discriminator Loss: 0.8049... Generator Loss: 0.8563
Epoch 1/1... Discriminator Loss: 0.6271... Generator Loss: 1.5635
Epoch 1/1... Discriminator Loss: 0.9191... Generator Loss: 1.0235
Epoch 1/1... Discriminator Loss: 0.4275... Generator Loss: 1.5884
Epoch 1/1... Discriminator Loss: 1.0890... Generator Loss: 0.7863
Epoch 1/1... Discriminator Loss: 0.9120... Generator Loss: 1.0500
Epoch 1/1... Discriminator Loss: 0.7754... Generator Loss: 1.2376
Epoch 1/1... Discriminator Loss: 0.6597... Generator Loss: 1.4850
Epoch 1/1... Discriminator Loss: 0.6716... Generator Loss: 1.4627
Epoch 1/1... Discriminator Loss: 0.6210... Generator Loss: 1.9104
Epoch 1/1... Discriminator Loss: 0.5371... Generator Loss: 1.7277
Epoch 1/1... Discriminator Loss: 0.5297... Generator Loss: 1.8127
Epoch 1/1... Discriminator Loss: 1.2377... Generator Loss: 0.4758
Epoch 1/1... Discriminator Loss: 0.6568... Generator Loss: 1.4647
Epoch 1/1... Discriminator Loss: 0.6494... Generator Loss: 1.1432
Epoch 1/1... Discriminator Loss: 0.5455... Generator Loss: 1.3737
Epoch 1/1... Discriminator Loss: 0.7573... Generator Loss: 1.3946
Epoch 1/1... Discriminator Loss: 0.9064... Generator Loss: 0.7939
Epoch 1/1... Discriminator Loss: 0.9301... Generator Loss: 0.7151
Epoch 1/1... Discriminator Loss: 0.7705... Generator Loss: 1.6095
Epoch 1/1... Discriminator Loss: 0.9067... Generator Loss: 0.9612
Epoch 1/1... Discriminator Loss: 0.7352... Generator Loss: 1.0227
Epoch 1/1... Discriminator Loss: 0.7464... Generator Loss: 1.4787
Epoch 1/1... Discriminator Loss: 0.8000... Generator Loss: 1.0388
Epoch 1/1... Discriminator Loss: 0.9447... Generator Loss: 0.7724
Epoch 1/1... Discriminator Loss: 0.9607... Generator Loss: 0.8034
Epoch 1/1... Discriminator Loss: 1.1911... Generator Loss: 0.5344
Epoch 1/1... Discriminator Loss: 1.0174... Generator Loss: 0.6830
Epoch 1/1... Discriminator Loss: 0.8903... Generator Loss: 1.3243
Epoch 1/1... Discriminator Loss: 0.4475... Generator Loss: 1.7063
Epoch 1/1... Discriminator Loss: 1.6840... Generator Loss: 0.2915
Epoch 1/1... Discriminator Loss: 1.0429... Generator Loss: 0.7637
Epoch 1/1... Discriminator Loss: 0.4403... Generator Loss: 1.9264
Epoch 1/1... Discriminator Loss: 0.9637... Generator Loss: 0.8080
Epoch 1/1... Discriminator Loss: 0.7674... Generator Loss: 1.0505
Epoch 1/1... Discriminator Loss: 0.8755... Generator Loss: 0.9567
Epoch 1/1... Discriminator Loss: 0.7255... Generator Loss: 1.3830
Epoch 1/1... Discriminator Loss: 1.0369... Generator Loss: 0.6261
Epoch 1/1... Discriminator Loss: 0.9209... Generator Loss: 0.9590
Epoch 1/1... Discriminator Loss: 0.9774... Generator Loss: 0.9074
Epoch 1/1... Discriminator Loss: 0.6051... Generator Loss: 1.3130
Epoch 1/1... Discriminator Loss: 0.8722... Generator Loss: 0.9526
Epoch 1/1... Discriminator Loss: 1.0448... Generator Loss: 0.6398
Epoch 1/1... Discriminator Loss: 0.8448... Generator Loss: 1.2032
Epoch 1/1... Discriminator Loss: 1.2253... Generator Loss: 0.5334
Epoch 1/1... Discriminator Loss: 1.1775... Generator Loss: 0.5052
Epoch 1/1... Discriminator Loss: 1.0262... Generator Loss: 0.7328
Epoch 1/1... Discriminator Loss: 1.0359... Generator Loss: 0.6642
Epoch 1/1... Discriminator Loss: 0.9939... Generator Loss: 0.7011
Epoch 1/1... Discriminator Loss: 0.8749... Generator Loss: 0.8310
Epoch 1/1... Discriminator Loss: 0.8756... Generator Loss: 0.7964
Epoch 1/1... Discriminator Loss: 0.9198... Generator Loss: 0.8376
Epoch 1/1... Discriminator Loss: 0.8911... Generator Loss: 0.7402
Epoch 1/1... Discriminator Loss: 1.3703... Generator Loss: 0.4154
Epoch 1/1... Discriminator Loss: 0.9452... Generator Loss: 1.0942
Epoch 1/1... Discriminator Loss: 0.8588... Generator Loss: 1.0112
Epoch 1/1... Discriminator Loss: 1.0116... Generator Loss: 0.9294
Epoch 1/1... Discriminator Loss: 0.8039... Generator Loss: 1.0401
Epoch 1/1... Discriminator Loss: 1.6652... Generator Loss: 0.3229
Epoch 1/1... Discriminator Loss: 0.6025... Generator Loss: 1.5853
Epoch 1/1... Discriminator Loss: 0.9640... Generator Loss: 0.7950
Epoch 1/1... Discriminator Loss: 0.6382... Generator Loss: 1.3869
Epoch 1/1... Discriminator Loss: 1.1637... Generator Loss: 0.5424
Epoch 1/1... Discriminator Loss: 0.7328... Generator Loss: 1.0500
Epoch 1/1... Discriminator Loss: 0.8364... Generator Loss: 1.0027
Epoch 1/1... Discriminator Loss: 0.8384... Generator Loss: 1.2413
Epoch 1/1... Discriminator Loss: 1.2588... Generator Loss: 0.4613
Epoch 1/1... Discriminator Loss: 0.7023... Generator Loss: 1.3046
Epoch 1/1... Discriminator Loss: 0.8742... Generator Loss: 0.9139
Epoch 1/1... Discriminator Loss: 0.9374... Generator Loss: 1.0857
Epoch 1/1... Discriminator Loss: 0.8981... Generator Loss: 1.5543
Epoch 1/1... Discriminator Loss: 0.6659... Generator Loss: 1.1887
Epoch 1/1... Discriminator Loss: 0.8623... Generator Loss: 0.8990
Epoch 1/1... Discriminator Loss: 0.7769... Generator Loss: 1.7151
Epoch 1/1... Discriminator Loss: 0.8252... Generator Loss: 0.9869
Epoch 1/1... Discriminator Loss: 1.0276... Generator Loss: 0.6999
Epoch 1/1... Discriminator Loss: 0.8914... Generator Loss: 0.8672
Epoch 1/1... Discriminator Loss: 0.8372... Generator Loss: 0.8537
Epoch 1/1... Discriminator Loss: 0.7133... Generator Loss: 1.0856
Epoch 1/1... Discriminator Loss: 1.0949... Generator Loss: 1.5053
Epoch 1/1... Discriminator Loss: 0.8986... Generator Loss: 1.0024
Epoch 1/1... Discriminator Loss: 0.7528... Generator Loss: 1.4657
Epoch 1/1... Discriminator Loss: 0.7208... Generator Loss: 1.1718
Epoch 1/1... Discriminator Loss: 0.6219... Generator Loss: 1.1863
Epoch 1/1... Discriminator Loss: 0.9651... Generator Loss: 0.9664
Epoch 1/1... Discriminator Loss: 0.7920... Generator Loss: 1.1854
Epoch 1/1... Discriminator Loss: 0.9010... Generator Loss: 0.8067
Epoch 1/1... Discriminator Loss: 0.9644... Generator Loss: 0.7867
Epoch 1/1... Discriminator Loss: 0.7935... Generator Loss: 0.9263
Epoch 1/1... Discriminator Loss: 1.1492... Generator Loss: 0.5474
Epoch 1/1... Discriminator Loss: 1.0174... Generator Loss: 1.0921
Epoch 1/1... Discriminator Loss: 0.7377... Generator Loss: 1.1926
Epoch 1/1... Discriminator Loss: 0.9291... Generator Loss: 0.9710
Epoch 1/1... Discriminator Loss: 0.5934... Generator Loss: 1.1740
Epoch 1/1... Discriminator Loss: 0.3426... Generator Loss: 2.3448
Epoch 1/1... Discriminator Loss: 1.3519... Generator Loss: 0.4053
Epoch 1/1... Discriminator Loss: 1.1939... Generator Loss: 0.5576
Epoch 1/1... Discriminator Loss: 0.8196... Generator Loss: 0.9345
Epoch 1/1... Discriminator Loss: 0.6637... Generator Loss: 1.5073
Epoch 1/1... Discriminator Loss: 1.2477... Generator Loss: 0.4689
Epoch 1/1... Discriminator Loss: 0.8439... Generator Loss: 1.0681
Epoch 1/1... Discriminator Loss: 0.7851... Generator Loss: 1.5286
Epoch 1/1... Discriminator Loss: 1.0363... Generator Loss: 1.3601
Epoch 1/1... Discriminator Loss: 0.6723... Generator Loss: 1.1216
Epoch 1/1... Discriminator Loss: 0.7254... Generator Loss: 1.4590
Epoch 1/1... Discriminator Loss: 0.8578... Generator Loss: 1.6869
Epoch 1/1... Discriminator Loss: 1.0577... Generator Loss: 0.8889
Epoch 1/1... Discriminator Loss: 1.0322... Generator Loss: 0.7359
Epoch 1/1... Discriminator Loss: 0.7666... Generator Loss: 1.2604
Epoch 1/1... Discriminator Loss: 0.7383... Generator Loss: 1.3097
Epoch 1/1... Discriminator Loss: 0.4926... Generator Loss: 2.1654
Epoch 1/1... Discriminator Loss: 2.0177... Generator Loss: 0.1845
Epoch 1/1... Discriminator Loss: 0.5933... Generator Loss: 1.1886
Epoch 1/1... Discriminator Loss: 1.8417... Generator Loss: 0.2853
Epoch 1/1... Discriminator Loss: 0.8461... Generator Loss: 0.8434
Epoch 1/1... Discriminator Loss: 0.7514... Generator Loss: 0.9694
Epoch 1/1... Discriminator Loss: 0.8758... Generator Loss: 0.9001
Epoch 1/1... Discriminator Loss: 0.6861... Generator Loss: 1.2194
Epoch 1/1... Discriminator Loss: 1.1043... Generator Loss: 0.6753
Epoch 1/1... Discriminator Loss: 1.2406... Generator Loss: 0.5014
Epoch 1/1... Discriminator Loss: 1.0771... Generator Loss: 0.7153
Epoch 1/1... Discriminator Loss: 1.0120... Generator Loss: 0.7644
Epoch 1/1... Discriminator Loss: 0.9475... Generator Loss: 0.8397
Epoch 1/1... Discriminator Loss: 0.4438... Generator Loss: 2.1682
Epoch 1/1... Discriminator Loss: 1.5613... Generator Loss: 0.3773
Epoch 1/1... Discriminator Loss: 0.9801... Generator Loss: 0.7990
Epoch 1/1... Discriminator Loss: 1.0952... Generator Loss: 0.8037
Epoch 1/1... Discriminator Loss: 0.7055... Generator Loss: 1.1855
Epoch 1/1... Discriminator Loss: 0.6103... Generator Loss: 1.4519
Epoch 1/1... Discriminator Loss: 1.0454... Generator Loss: 0.8769
Epoch 1/1... Discriminator Loss: 0.3961... Generator Loss: 1.7438
Epoch 1/1... Discriminator Loss: 1.3057... Generator Loss: 0.4308
Epoch 1/1... Discriminator Loss: 1.0564... Generator Loss: 0.7566
Epoch 1/1... Discriminator Loss: 0.9925... Generator Loss: 0.7983
Epoch 1/1... Discriminator Loss: 0.9782... Generator Loss: 1.0198
Epoch 1/1... Discriminator Loss: 0.9136... Generator Loss: 1.2890
Epoch 1/1... Discriminator Loss: 1.0302... Generator Loss: 0.6175
Epoch 1/1... Discriminator Loss: 1.0247... Generator Loss: 0.7006
Epoch 1/1... Discriminator Loss: 1.6942... Generator Loss: 0.3562
Epoch 1/1... Discriminator Loss: 1.1143... Generator Loss: 0.7362
Epoch 1/1... Discriminator Loss: 0.9273... Generator Loss: 0.8148
Epoch 1/1... Discriminator Loss: 0.7704... Generator Loss: 0.9493
Epoch 1/1... Discriminator Loss: 0.8565... Generator Loss: 0.8996
Epoch 1/1... Discriminator Loss: 1.1580... Generator Loss: 0.5779
Epoch 1/1... Discriminator Loss: 0.9074... Generator Loss: 0.8335
Epoch 1/1... Discriminator Loss: 0.6140... Generator Loss: 1.3035
Epoch 1/1... Discriminator Loss: 0.8443... Generator Loss: 0.9520
Epoch 1/1... Discriminator Loss: 0.4983... Generator Loss: 1.5237
Epoch 1/1... Discriminator Loss: 0.9664... Generator Loss: 0.6835
Epoch 1/1... Discriminator Loss: 0.9781... Generator Loss: 0.9250
Epoch 1/1... Discriminator Loss: 1.1158... Generator Loss: 0.6026
Epoch 1/1... Discriminator Loss: 0.9263... Generator Loss: 0.7750
Epoch 1/1... Discriminator Loss: 1.3675... Generator Loss: 0.4167
Epoch 1/1... Discriminator Loss: 0.9077... Generator Loss: 0.8328
Epoch 1/1... Discriminator Loss: 1.1284... Generator Loss: 0.5701
Epoch 1/1... Discriminator Loss: 0.9608... Generator Loss: 0.9727
Epoch 1/1... Discriminator Loss: 0.6881... Generator Loss: 1.1705
Epoch 1/1... Discriminator Loss: 0.6779... Generator Loss: 1.2260
Epoch 1/1... Discriminator Loss: 0.7581... Generator Loss: 1.1990
Epoch 1/1... Discriminator Loss: 1.3065... Generator Loss: 0.4269
Epoch 1/1... Discriminator Loss: 0.5907... Generator Loss: 1.4416
Epoch 1/1... Discriminator Loss: 1.0831... Generator Loss: 0.6277
Epoch 1/1... Discriminator Loss: 0.3749... Generator Loss: 1.7775
Epoch 1/1... Discriminator Loss: 0.9381... Generator Loss: 0.7595
Epoch 1/1... Discriminator Loss: 0.8596... Generator Loss: 1.6188
Epoch 1/1... Discriminator Loss: 1.0035... Generator Loss: 0.6742
Epoch 1/1... Discriminator Loss: 0.6116... Generator Loss: 1.3928
Epoch 1/1... Discriminator Loss: 0.6872... Generator Loss: 1.3277
Epoch 1/1... Discriminator Loss: 0.8399... Generator Loss: 0.8721
Epoch 1/1... Discriminator Loss: 0.8688... Generator Loss: 1.1897
Epoch 1/1... Discriminator Loss: 0.9043... Generator Loss: 1.7545
Epoch 1/1... Discriminator Loss: 0.8203... Generator Loss: 0.8885
Epoch 1/1... Discriminator Loss: 0.6785... Generator Loss: 0.9986
Epoch 1/1... Discriminator Loss: 0.9926... Generator Loss: 0.9360
Epoch 1/1... Discriminator Loss: 0.6707... Generator Loss: 1.3318
Epoch 1/1... Discriminator Loss: 0.8088... Generator Loss: 1.1297
Epoch 1/1... Discriminator Loss: 0.9671... Generator Loss: 0.7400
Epoch 1/1... Discriminator Loss: 0.5612... Generator Loss: 1.6559
Epoch 1/1... Discriminator Loss: 0.7755... Generator Loss: 1.6778
Epoch 1/1... Discriminator Loss: 1.2683... Generator Loss: 1.0013
Epoch 1/1... Discriminator Loss: 0.8256... Generator Loss: 1.1810
Epoch 1/1... Discriminator Loss: 0.8093... Generator Loss: 1.3830
Epoch 1/1... Discriminator Loss: 0.7043... Generator Loss: 0.9030
Epoch 1/1... Discriminator Loss: 1.1716... Generator Loss: 0.5676
Epoch 1/1... Discriminator Loss: 0.4588... Generator Loss: 2.2051
Epoch 1/1... Discriminator Loss: 0.6459... Generator Loss: 2.0004
Epoch 1/1... Discriminator Loss: 0.6158... Generator Loss: 1.1950
Epoch 1/1... Discriminator Loss: 0.6665... Generator Loss: 1.2685
Epoch 1/1... Discriminator Loss: 0.4933... Generator Loss: 1.8817
Epoch 1/1... Discriminator Loss: 0.6692... Generator Loss: 1.1070
Epoch 1/1... Discriminator Loss: 0.8076... Generator Loss: 1.6346
Epoch 1/1... Discriminator Loss: 0.3329... Generator Loss: 1.8091
Epoch 1/1... Discriminator Loss: 1.1245... Generator Loss: 0.7240
Epoch 1/1... Discriminator Loss: 0.7559... Generator Loss: 1.3360
Epoch 1/1... Discriminator Loss: 0.9021... Generator Loss: 0.8529
Epoch 1/1... Discriminator Loss: 0.8237... Generator Loss: 1.0514
Epoch 1/1... Discriminator Loss: 1.3492... Generator Loss: 0.4125
Epoch 1/1... Discriminator Loss: 0.7655... Generator Loss: 1.1937
Epoch 1/1... Discriminator Loss: 0.4669... Generator Loss: 1.6841
Epoch 1/1... Discriminator Loss: 0.9905... Generator Loss: 0.7188
Epoch 1/1... Discriminator Loss: 0.8527... Generator Loss: 0.8862
Epoch 1/1... Discriminator Loss: 0.5582... Generator Loss: 1.5870
Epoch 1/1... Discriminator Loss: 1.0350... Generator Loss: 0.6847
Epoch 1/1... Discriminator Loss: 0.9050... Generator Loss: 1.1134
Epoch 1/1... Discriminator Loss: 1.6051... Generator Loss: 0.3281
Epoch 1/1... Discriminator Loss: 0.7896... Generator Loss: 0.9984
Epoch 1/1... Discriminator Loss: 0.8966... Generator Loss: 1.2430
Epoch 1/1... Discriminator Loss: 0.6528... Generator Loss: 1.1692
Epoch 1/1... Discriminator Loss: 0.9030... Generator Loss: 1.0867
Epoch 1/1... Discriminator Loss: 1.0581... Generator Loss: 0.8320
Epoch 1/1... Discriminator Loss: 0.6944... Generator Loss: 1.3573
Epoch 1/1... Discriminator Loss: 0.6844... Generator Loss: 1.2405
Epoch 1/1... Discriminator Loss: 0.9276... Generator Loss: 0.7701
Epoch 1/1... Discriminator Loss: 0.7039... Generator Loss: 1.2072
Epoch 1/1... Discriminator Loss: 1.0063... Generator Loss: 1.3639
Epoch 1/1... Discriminator Loss: 1.1583... Generator Loss: 0.5013
Epoch 1/1... Discriminator Loss: 1.4242... Generator Loss: 0.3953
Epoch 1/1... Discriminator Loss: 0.8724... Generator Loss: 0.8324
Epoch 1/1... Discriminator Loss: 0.8300... Generator Loss: 1.1385
Epoch 1/1... Discriminator Loss: 0.8695... Generator Loss: 0.8508
Epoch 1/1... Discriminator Loss: 0.4649... Generator Loss: 1.9265
Epoch 1/1... Discriminator Loss: 0.9191... Generator Loss: 1.0482
Epoch 1/1... Discriminator Loss: 1.1389... Generator Loss: 0.5535
Epoch 1/1... Discriminator Loss: 0.7911... Generator Loss: 0.9974
Epoch 1/1... Discriminator Loss: 0.9976... Generator Loss: 0.9991
Epoch 1/1... Discriminator Loss: 0.8038... Generator Loss: 1.0031
Epoch 1/1... Discriminator Loss: 0.6825... Generator Loss: 1.2919
Epoch 1/1... Discriminator Loss: 1.0815... Generator Loss: 0.7291
Epoch 1/1... Discriminator Loss: 0.7270... Generator Loss: 1.1079
Epoch 1/1... Discriminator Loss: 0.7698... Generator Loss: 1.1587
Epoch 1/1... Discriminator Loss: 0.8378... Generator Loss: 0.9281
Epoch 1/1... Discriminator Loss: 0.9675... Generator Loss: 1.2206
Epoch 1/1... Discriminator Loss: 0.7257... Generator Loss: 1.2816
Epoch 1/1... Discriminator Loss: 0.8813... Generator Loss: 0.9214
Epoch 1/1... Discriminator Loss: 0.8068... Generator Loss: 1.3107
Epoch 1/1... Discriminator Loss: 1.0050... Generator Loss: 1.3585
Epoch 1/1... Discriminator Loss: 0.5682... Generator Loss: 1.4839
Epoch 1/1... Discriminator Loss: 0.3633... Generator Loss: 1.8104
Epoch 1/1... Discriminator Loss: 0.8662... Generator Loss: 0.8787
Epoch 1/1... Discriminator Loss: 0.7252... Generator Loss: 1.5948
Epoch 1/1... Discriminator Loss: 0.5737... Generator Loss: 2.0902
Epoch 1/1... Discriminator Loss: 1.0539... Generator Loss: 0.8400
Epoch 1/1... Discriminator Loss: 0.9326... Generator Loss: 0.9576
Epoch 1/1... Discriminator Loss: 0.8763... Generator Loss: 0.9496
Epoch 1/1... Discriminator Loss: 0.5490... Generator Loss: 1.5650
Epoch 1/1... Discriminator Loss: 0.8491... Generator Loss: 0.8685
Epoch 1/1... Discriminator Loss: 0.9118... Generator Loss: 0.8366
Epoch 1/1... Discriminator Loss: 0.3425... Generator Loss: 2.1987
Epoch 1/1... Discriminator Loss: 0.7225... Generator Loss: 1.2008
Epoch 1/1... Discriminator Loss: 0.9914... Generator Loss: 0.7455
Epoch 1/1... Discriminator Loss: 0.6174... Generator Loss: 1.2974
Epoch 1/1... Discriminator Loss: 0.6331... Generator Loss: 1.4597
Epoch 1/1... Discriminator Loss: 1.1048... Generator Loss: 0.6727
Epoch 1/1... Discriminator Loss: 0.9053... Generator Loss: 1.3592
Epoch 1/1... Discriminator Loss: 0.9579... Generator Loss: 1.0121
Epoch 1/1... Discriminator Loss: 1.0162... Generator Loss: 2.1694
Epoch 1/1... Discriminator Loss: 0.6707... Generator Loss: 1.9337
Epoch 1/1... Discriminator Loss: 0.7923... Generator Loss: 1.1842
Epoch 1/1... Discriminator Loss: 1.0013... Generator Loss: 0.8041
Epoch 1/1... Discriminator Loss: 0.6090... Generator Loss: 1.3978
Epoch 1/1... Discriminator Loss: 0.6538... Generator Loss: 1.5943
Epoch 1/1... Discriminator Loss: 0.6902... Generator Loss: 1.3644
Epoch 1/1... Discriminator Loss: 0.8626... Generator Loss: 1.1592
Epoch 1/1... Discriminator Loss: 0.8986... Generator Loss: 0.7669
Epoch 1/1... Discriminator Loss: 0.3169... Generator Loss: 2.1531
Epoch 1/1... Discriminator Loss: 0.9031... Generator Loss: 0.8905
Epoch 1/1... Discriminator Loss: 0.6492... Generator Loss: 1.5102
Epoch 1/1... Discriminator Loss: 1.0674... Generator Loss: 0.6040
Epoch 1/1... Discriminator Loss: 0.7212... Generator Loss: 0.9718
Epoch 1/1... Discriminator Loss: 0.9085... Generator Loss: 1.3302
Epoch 1/1... Discriminator Loss: 1.0591... Generator Loss: 0.7403
Epoch 1/1... Discriminator Loss: 1.0442... Generator Loss: 0.6093
Epoch 1/1... Discriminator Loss: 1.4288... Generator Loss: 1.5898
Epoch 1/1... Discriminator Loss: 0.7866... Generator Loss: 1.1216
Epoch 1/1... Discriminator Loss: 0.7771... Generator Loss: 0.9780
Epoch 1/1... Discriminator Loss: 0.7810... Generator Loss: 0.9988
Epoch 1/1... Discriminator Loss: 0.9232... Generator Loss: 0.7137
Epoch 1/1... Discriminator Loss: 0.4330... Generator Loss: 2.3691
Epoch 1/1... Discriminator Loss: 0.7928... Generator Loss: 1.0384
Epoch 1/1... Discriminator Loss: 1.0686... Generator Loss: 0.5836
Epoch 1/1... Discriminator Loss: 1.1123... Generator Loss: 0.5803
Epoch 1/1... Discriminator Loss: 0.8459... Generator Loss: 1.4931
Epoch 1/1... Discriminator Loss: 0.9409... Generator Loss: 0.7463
Epoch 1/1... Discriminator Loss: 1.3695... Generator Loss: 0.3992
Epoch 1/1... Discriminator Loss: 1.0564... Generator Loss: 1.3377
Epoch 1/1... Discriminator Loss: 0.7972... Generator Loss: 1.1683
Epoch 1/1... Discriminator Loss: 0.7507... Generator Loss: 0.9244
Epoch 1/1... Discriminator Loss: 0.8680... Generator Loss: 1.0061
Epoch 1/1... Discriminator Loss: 1.0150... Generator Loss: 0.8130
Epoch 1/1... Discriminator Loss: 0.7796... Generator Loss: 1.0513
Epoch 1/1... Discriminator Loss: 0.8698... Generator Loss: 0.9571
Epoch 1/1... Discriminator Loss: 0.7861... Generator Loss: 0.8974
Epoch 1/1... Discriminator Loss: 0.7074... Generator Loss: 1.0372
Epoch 1/1... Discriminator Loss: 0.9498... Generator Loss: 0.8678
Epoch 1/1... Discriminator Loss: 0.9585... Generator Loss: 0.7355
Epoch 1/1... Discriminator Loss: 0.7214... Generator Loss: 1.4115
Epoch 1/1... Discriminator Loss: 1.5040... Generator Loss: 0.3675
Epoch 1/1... Discriminator Loss: 1.1619... Generator Loss: 0.5956
Epoch 1/1... Discriminator Loss: 1.1248... Generator Loss: 0.6243
Epoch 1/1... Discriminator Loss: 0.6835... Generator Loss: 1.0962
Epoch 1/1... Discriminator Loss: 0.8818... Generator Loss: 0.8732
Epoch 1/1... Discriminator Loss: 0.5534... Generator Loss: 1.8276
Epoch 1/1... Discriminator Loss: 1.1527... Generator Loss: 0.6504
Epoch 1/1... Discriminator Loss: 1.5364... Generator Loss: 0.3237
Epoch 1/1... Discriminator Loss: 1.2209... Generator Loss: 0.4893
Epoch 1/1... Discriminator Loss: 0.5602... Generator Loss: 1.3250
Epoch 1/1... Discriminator Loss: 0.7606... Generator Loss: 0.9790
Epoch 1/1... Discriminator Loss: 0.7903... Generator Loss: 0.8786
Epoch 1/1... Discriminator Loss: 0.2929... Generator Loss: 2.2314
Epoch 1/1... Discriminator Loss: 0.7691... Generator Loss: 1.4109
Epoch 1/1... Discriminator Loss: 0.9243... Generator Loss: 1.7020
Epoch 1/1... Discriminator Loss: 0.4765... Generator Loss: 1.9228
Epoch 1/1... Discriminator Loss: 1.0949... Generator Loss: 0.6063
Epoch 1/1... Discriminator Loss: 0.9106... Generator Loss: 0.8833
Epoch 1/1... Discriminator Loss: 1.2686... Generator Loss: 0.4391
Epoch 1/1... Discriminator Loss: 0.9350... Generator Loss: 0.7781
Epoch 1/1... Discriminator Loss: 1.9591... Generator Loss: 0.2087
Epoch 1/1... Discriminator Loss: 1.1182... Generator Loss: 0.7807
Epoch 1/1... Discriminator Loss: 0.8542... Generator Loss: 1.0339
Epoch 1/1... Discriminator Loss: 0.7568... Generator Loss: 1.3162
Epoch 1/1... Discriminator Loss: 0.9042... Generator Loss: 0.9496
Epoch 1/1... Discriminator Loss: 0.6208... Generator Loss: 1.9884
Epoch 1/1... Discriminator Loss: 0.9419... Generator Loss: 0.8440
Epoch 1/1... Discriminator Loss: 0.5493... Generator Loss: 1.3961
Epoch 1/1... Discriminator Loss: 1.0897... Generator Loss: 0.7218
Epoch 1/1... Discriminator Loss: 0.8023... Generator Loss: 0.8853
Epoch 1/1... Discriminator Loss: 1.1880... Generator Loss: 0.5044
Epoch 1/1... Discriminator Loss: 1.4020... Generator Loss: 0.3998
Epoch 1/1... Discriminator Loss: 1.0665... Generator Loss: 0.6016
Epoch 1/1... Discriminator Loss: 0.7544... Generator Loss: 1.4786
Epoch 1/1... Discriminator Loss: 0.7108... Generator Loss: 1.1538
Epoch 1/1... Discriminator Loss: 1.0732... Generator Loss: 0.6785
Epoch 1/1... Discriminator Loss: 0.4628... Generator Loss: 1.3892
Epoch 1/1... Discriminator Loss: 1.1752... Generator Loss: 0.5703
Epoch 1/1... Discriminator Loss: 1.1137... Generator Loss: 0.6189
Epoch 1/1... Discriminator Loss: 1.0564... Generator Loss: 0.7182
Epoch 1/1... Discriminator Loss: 0.9011... Generator Loss: 0.9072
Epoch 1/1... Discriminator Loss: 0.4931... Generator Loss: 1.6940
Epoch 1/1... Discriminator Loss: 0.5722... Generator Loss: 1.8093
Epoch 1/1... Discriminator Loss: 0.5929... Generator Loss: 1.1364
Epoch 1/1... Discriminator Loss: 0.7548... Generator Loss: 1.9935
Epoch 1/1... Discriminator Loss: 0.3558... Generator Loss: 2.4018
Epoch 1/1... Discriminator Loss: 0.8093... Generator Loss: 0.9518
Epoch 1/1... Discriminator Loss: 0.8112... Generator Loss: 0.8914
Epoch 1/1... Discriminator Loss: 1.0928... Generator Loss: 0.5807
Epoch 1/1... Discriminator Loss: 0.7973... Generator Loss: 1.9723
Epoch 1/1... Discriminator Loss: 0.7644... Generator Loss: 1.4752
Epoch 1/1... Discriminator Loss: 0.7142... Generator Loss: 1.0812
Epoch 1/1... Discriminator Loss: 0.6339... Generator Loss: 1.4334
Epoch 1/1... Discriminator Loss: 1.0505... Generator Loss: 0.5983
Epoch 1/1... Discriminator Loss: 0.7444... Generator Loss: 1.2116

提交项目

提交本项目前,确保运行所有 cells 后保存该文件。

保存该文件为 "dlnd_face_generation.ipynb", 并另存为 HTML 格式 "File" -> "Download as"。提交项目时请附带 "helper.py" 和 "problem_unittests.py" 文件。